1. Field of the Invention
The present invention relates to a surface inspection device for inspecting the rough surface of a sample, and more particularly to a surface inspection device that inspects the microscopic surface contamination of a sample such as an IC (Integrated Circuit) chip or a processed Silicon wafer or a contact device.
2. Description of the Related Art
In a conventional fabrication process of a semiconductor device, wiring or bonding metal pads have been formed as fine patterns on the surface of a semiconductor chip, and the metal pads are connected to bonding wires or the connection terminals of chip components. Masking materials are applied to the surface of metal pads in the fabrication process, and because this material may hinder electrical connections, cleaning is carried out to remove all traces of the material.
Still, the microscopically rough surface of metal pads complicates the total cleaning of minute contamination from the surface. When the surface of metal pads are contaminated during the fabrication process, this contamination impedes electrical connections and causes insufficient bonding. It is therefore vital in fabricating semiconductor devices to inspect and analyze contamination on the surface of metal pad, investigate the sources of contamination, and then take measures to improve the yield rate of the semiconductor devices.
However, the analysis of minute contamination on the surface of metal pads are made difficult by the microscopically rough surface, as well as their small dimensions. Satisfactory analysis is particularly difficult in cases in which the contaminant is a mixture of organic and inorganic substances.
At present, surface inspection on the nano-scale is presently being carried out using STM (Scanning Tunneling Microscope) or AFM (Atomic Force Microscope) as the basic research in surface inspection of fine structure as described above. Unfortunately, this approach is impractical because it entails considerable time and expense.
Surface inspection is also carried out by a FTIR (Fourier Transform Infrared) spectroscope, which employs the absorption of infrared rays. However, microanalysis by this method is difficult and operation is also complex, and the considerable time and expense thus required for analysis render this method impractical.
One surface inspection method that solves the above-described problems involves analysis by polarized light (ellipsometry), in which surface inspection is realized by irradiating rays onto the surface of a sample to cause reflection and then analyzing the polarized light components of the reflected rays. This method allows microanalysis and simplifies operation.
Ellipsometry allows easy inspection of the surface of a sample but presupposes that the surface of the sample to be inspected is a mirror surface. If the sample is an integrated circuit during fabrication, however, fine metal pads are formed on the mirror surface of a semiconductor wafer by means of sputtering or electroplating, and the surface of the sample becames therefore microscopically rough.
If ellipsometry of the prior art is applied to the surface of this type of sample, accurate inspection is complicated by the diffused reflection of the rays caused by the microscopic bumps and depressions of the surface of the sample. In other words, the surface contamination of the sample, i.e., an integrated circuit during fabrication, cannot be inspected, and the method cannot provide an improvement in the yield rate of integrated circuits.
In addition, defects that occur in the surface of an integrated circuit during fabrication include contamination by inorganic substances, contamination by organic substances, contamination by mixtures of organic and inorganic substances, and the adhesion of extraneous matter. Inspection that can distinguish between these various defects was difficult in the ellipsometry of the prior art.
It is an object according to the present invention to provide a surface inspection method and device that allow satisfactory inspection and analysis of the surface of a sample such as a semiconductor wafer on which metal pads have been formed without requiring considerable time and expense.
According to one surface inspection method according to the present invention, two-dimensional scanning is effected by irradiating a focused laser beam onto the surface of a sample and then individually detecting the intensities of each of the s-polarized light component and p-polarized light component of the laser beam reflected by each location of the two-dimensionally scanned surface of the sample. The RR (Reflectance Ratio), which is the ratio of the reflected intensities of the detected s-polarized light component and p-polarized light component, is observed for each location of the sample surface, and the distribution of the observed RR on the sample surface is measured. This measured RR distribution width is then compared with the natural width of a clean sample, and the sample surface is determined to be contaminated when, as the comparison results, the RR distribution width diverges from the natural width. In the surface inspection method of this invention, the presence or absence of contamination on the microscopically rough surface of the sample can therefore be accurately and easily determined based on the RR of the reflected intensities of s- and p-polarized light.
The basic principles of the above-described invention are explained hereinbelow. First, in a case in which the sample is the metal pad of a mass-produced circuit component, the sample surface is not microscopically smooth, and the reflection of a laser beam irradiating this surface is generally diffuse. The reflected intensities Ros and Rop of the s- and p-polarized light can be approximately assumed in this invention as shown below:
Ros=Rouxc3x97Rsxe2x80x83xe2x80x83(1a) 
Rop=Rouxc3x97Rpxe2x80x83xe2x80x83(1b) 
where Rou is a specular reflective power on a rough surface, and Rs and Rp are the amplitude reflectances of s- and p-polarized light on an ideally smooth surface observed by means of a Drude reflection equation or a Fresnel reflection equation.
If the sample surface is unevenly contaminated, reflectances Rs and Rp of s- and p-polarized light are subject to complex modification. The ratio of reflective intensities Ros and Rop by the above-described equations (1a) and (1b) becomes the ratio RR of reflective intensities of s- and p-polarized light as shown in the following equation (2):
RR=Ros/Rop=(Rouxc3x97Rs)/(Rouxc3x97Rp)=Rs/Rpxe2x80x83xe2x80x83(2) 
This ratio RR is independent of the roughness of the sample surface and the characteristic of the device cancel each other out. However, the s-polarized light and p-polarized light differ from each other in their interaction with the physical surface of the electric vector of light, and the proportion of change in reflective intensity of the s-polarized and p-polarized light due to contaminants is therefore not identical.
In this invention, the state of the sample surface is analyzed using the above-described equation (2) because the use of RR allows the state of contamination to be detected while excluding the effect of the roughness of the sample surface.
The numerical value of the ratio Rs/Rp for the case of a clean sample surface is calculated as a theoretical value from the dielectric constant of the material or the angle of incidence of the beam using a Fresnel reflection equation. If, for example, the angle of incidence is 60xc2x0, the theoretical value of RR for gold is 1.09 and 1.95 for rhodium. The state of contamination of the sample surface can be determined by comparison with actually measured values for ratio RR.
The natural width of a clean sample referred to in this invention indicates the distribution width for a case in which RR is determined by detecting the reflective intensities of the s-polarized light component and p-polarized light component for a clean sample surface. This distribution width indicates the width over which the distribution of RR can be compared, and for example, may be the half-width.
According to another surface inspection method of the invention, the distribution of RR on a sample surface is detected as in the above-described surface inspection method of the invention, and the layer thickness of contamination on the sample surface is detected based on the half-width of this measured RR distribution. The surface inspection method of this invention therefore allows accurate and easy determination of the layer thickness of contamination on the microscopically rough surface of the sample based on the RR of the reflective intensities of s- and p-polarized light.
According to yet another surface inspection method of the invention, the distribution of RR on the sample surface is detected as in the above-described surface inspection method of the invention, the central value of this measured RR distribution is compared with a theoretical value observed by means of a Fresnel reflection equation, and the sample surface is determined to be contaminated when, as the result of comparison, the central value of the RR distribution diverges from the theoretical value. The surface inspection method of the invention therefore enables easy and accurate determination of the presence or absence of contamination on the microscopically rough surface of the sample based on the RR of the reflective intensities of the s- and p-polarized light.
According to still another surface inspection method of the invention, the central value of RR distribution is compared with a theoretical value observed by a Fresnel reflection equation as in the above-described surface inspection method of the invention, and the surface of the sample is determined to be contaminated by a single substance when, as the result of comparison, the central value of RR distribution is greater than the theoretical value, and determined to be contaminated by a mixture of substances when the central value of RR distribution is less than the theoretical value. The surface inspection method of the invention therefore determines if the substance that contaminates the microscopically rough surface of the sample is a single substance or a mixture of substances based on the RR of the reflective intensities of the s- and p-polarized light.
In one surface inspection device of the invention, a laser beam is focused and irradiated by a laser irradiating device onto the surface of a sample held by a sample holding structure, and at least one of the laser irradiating device and sample holding structure in this state is moved by a relative scanning structure such that the laser beam irradiating the sample scans two-dimensionally. A polarized light detector individually detects the intensities of each of the s-polarized light component and p-polarized light component of the laser beam reflected by each location of the surface of the sample that is scanned two-dimensionally in this way. A ratio observing means observes RR, which is the ratio of the reflective intensities of the s-polarized light component and p-polarized light component for each location of the sample surface, and a distribution detecting means detects the two-dimensional distribution of the observed RR on the surface of the sample. A numerical value comparing means compares the distribution width of RR detected by the distribution detecting means with the natural width of a clean sample, and when, as the result of comparison of this numerical value comparing means, the RR distribution width diverges from the natural width, a contamination judging means determines that the surface of the sample is contaminated. The presence or absence of contamination of the microscopically rough surface of a sample can therefore be determined quickly and easily.
In a surface inspection device according to the foregoing description, the numerical value comparing means may also compare a natural width with the half-width of the RR distribution, which indicates the contamination of the surface of a sample. In this case, the presence or absence of contamination of the surface of the sample can be determined simply and accurately.
In the surface inspection device according to the foregoing description, a layer thickness inspecting means may also detect the layer thickness of contamination on the surface of the sample based on the half-width of the RR distribution detected by the distribution detecting means. In this case, the degree of contamination of the surface of the sample can be determined accurately.
According to another surface inspection device of the invention, a distribution detecting means detects the two-dimensional distribution of RR on the surface of a sample as in the surface inspection device of the invention in the foregoing description, and a numerical value comparing means compares the central value of the RR distribution detected by this distribution detecting means with a theoretical value observed using a Fresnel reflection equation. The contamination judging means determines that the surface of the sample is contaminated when, as the result of comparison of this numerical value comparing means, the central value of RR distribution diverges from a theoretical value. The presence or absence of contamination on the microscopically rough surface of a sample therefore can be determined quickly and easily based on the RR of reflective intensities of the s- and p-polarized light.
In the above-described surface inspection device, it is possible to determine that the surface of the sample is contaminated by a single substance when the central value of the RR distribution is greater than the theoretical value, and contaminated by a mixture of substances when the central value of the RR distribution is lower. In this case, the substance that contaminates the surface of a sample can be determined to be a single substance or a mixture of substances.
In the above-described surface inspection device, it is also possible for an image displaying means to display various data determined based on the RR distribution as an image that corresponds to the surface of a sample. In this case, the two-dimensional contamination of the surface of a sample can be confirmed by means of the displayed image.
According to yet another surface inspection device of the invention, a ratio observing means observes RR for each analyzed region of the surface of a sample as in the above-described surface inspection device of the invention, a frequency detecting means then detects the frequency of occurrence of each value of this observed RR for each prescribed analyzed partition made up of a plurality of analyzed regions, and based on these detection results, a relation detecting means detects the correlation between each value of RR and the frequency of occurrence for each analyzed partition of the sample surface.
This correlation represents the frequency of occurrence of each value of RR in a prescribed analyzed partition of the sample surface and reflects the state of contamination of the sample surface, and the state of contamination of the sample surface therefore can be detected from the above-described correlation. The effect of the microscopic roughness of the surface of a sample can be canceled because this correlation is detected based on RR, which is the ratio of the reflective intensities of the s-polarized light component and p-polarized light component, and the state of contamination of the surface of a sample can be detected quickly and with good accuracy.
According to still another surface inspection device of the invention, a ratio observing means observes RR for each analyzed region of the surface of a sample as in the above-described surface inspection device of the invention, and a relation detecting means then detects the correlation between each value of the thus-observed RR and a plurality of analyzed regions for each analyzed partition. This correlation represents the frequency of occurrence of each value of RR in a prescribed analyzed partition of the surface of a sample and indicates the state of contamination of the sample surface, and the state of contamination of the surface of a sample can therefore be detected by means of the above-described correlation. The effect of the microscopic roughness of the surface of a sample can be canceled because this correlation is detected based on RR, which is the ratio of the reflective intensities of s-polarized light component and a p-polarized light component, and the state of contamination of the sample surface can therefore be detected quickly and with good accuracy.
In the above-described surface inspection device, a relation detecting means may also generate a two-dimensional graph in which one of the frequency of occurrence and each value of RR is plotted on the vertical axis and the other is plotted on the horizontal axis, and an image displaying means may display the two-dimensional graph generated by this relation detecting means. In this case, the state of contamination of the surface of a sample is displayed as a two-dimensional graph, and the state of contamination of the surface of a sample therefore can be confirmed at a glance by an operator.
In a surface inspection device according to the foregoing description, the relation detecting means may generate a three-dimensional graph in which the analyzed partition is the lower plane and the value of RR for each analyzed region is plotted on the vertical axis, and an image displaying means may display the three-dimensional graph generated by the relation detecting means. In this case, the state of contamination of the surface of the sample is displayed as a three-dimensional graph, and the state of contamination of the sample surface therefore can be confirmed at a glance by an operator.
In a surface inspection device according to the foregoing description, the relation detecting means may generate a two-dimensional graph in which the analyzed partition is represented as a plane and the value of RR for each analyzed region is represented as a prescribed color, and the image displaying means displays the two-dimensional graph generated by the relation detecting means. In this case, the state of contamination of the surface of a sample is displayed as a two-dimensional graph, and the state of contamination of the sample surface therefore can be confirmed at a glance by an operator.
Generally, if the surface of a sample is clean, only specific numerical values of RR are generated at high frequency in concentrations. The sharp decrease in the frequency of occurrence of numerical values diverging from these specific values results in, for example, the steep shape of the curve of a two-dimensional graph.
In contrast, contamination of the surface of a sample brings about changes in the numerical values of RR that are generated at high frequency, and the frequency of occurrence of numerical values that diverge from this numerical value also exhibits a relative increase. As a result, the curve in a two-dimensional graph becomes less steep.
In addition, when the surface of a sample is contaminated as described above, the numerical values of RR that are generated at high frequency also undergo an overall change, and the position of the range in which a numerical values of RR are generated at a prescribed frequency also changes. The numerical values of RR that are generated at high frequency increase when the contamination of the sample surface is inorganic, and the numerical values of RR decrease when the contaminant is organic.
As described in the foregoing explanation, the surface inspection device detects the correlation between the frequency of occurrence and the value of RR for each analyzed partition of a sample surface, or the correlation between the plurality of analyzed regions that make up a prescribed analyzed partition and each value of RR. If these detection results are displayed as a two-dimensional graph or three dimensional graph, the state of contamination of the surface of a sample can be determined from the displayed image.
In a surface inspection method realized by a surface inspection device as described hereinabove, the presence or absence of contamination of the surface of a sample can be determined from the frequency of occurrence of specific numerical values of RR. In this case, the presence or absence of contamination of the sample surface can be determined quickly, easily and with good accuracy.
In addition, the presence or absence of contamination on the surface of a sample can be determined based on the size of the range in which numerical values of RR are generated at a prescribed frequency. In this case, the presence or absence of contamination on the surface of a sample can be determined quickly, easily, and with good accuracy.
In addition, the contamination of a sample can be determined to be caused by an inorganic material when the numerical value of RR at which the frequency of occurrence reaches a peak is higher than a reference numerical value, or caused by an organic material when lower than a reference numerical value. In this case, it can be determined quickly, easily, and with good accuracy whether contamination on the surface of a sample is organic or inorganic.
The contamination of a sample can also be determined as due to an inorganic substance if the position of the range in which a numerical value of RR is generated at a prescribed frequency is higher than a reference position, and due to an organic substance when the position is lower. In this case, it can be determined quickly, easily, and with good accuracy whether contamination on the surface of a sample is organic or inorganic.
Contamination of a sample can also be determined as due to a mixture of organic and inorganic substances if the position of the range in which a numerical value of RR is generated at a prescribed frequency is broader than a reference range. In this case, it can be determined quickly, easily, and with good accuracy that the surface of a sample is contaminated by a mixture of organic and inorganic substances.
As a surface inspection device of the invention that realizes the surface inspection method described hereinabove, the contamination judging means may determine the presence or absence of contamination on the surface of a sample based on the detection results of the relation detecting means. In this case, the surface inspection device can automatically determine the state of contamination of the surface of a sample.
The above-described contamination judging means may also determine if the contamination of a sample is due to an inorganic substance, an organic substance, or a mixture based on the detection results of the relation detecting means. In this case, the surface inspection device can automatically determine the type of contamination of the surface of a sample.
In the above-described surface inspection device, moreover, an intensity comparing means may compare the reflective intensity of the s-polarized light component detected by a polarized light detector with a prescribed reference intensity, and when, as the result of comparison, the reflective intensity is lower than the reference intensity, an extraneous material judging means may determine that extraneous material exists in an analyzed partition of the sample surface. In this case, extraneous matter can be detected in a case in which extraneous matter exists in an analyzed partition of the sample surface.
If the presence or absence of extraneous matter is determined for each analyzed partition in this way and if, for example, 400 analyzed regions exist in one analyzed partition, it is preferable that extraneous matter be judged not to exist even though the reflective intensity of the s-polarized light component is lower than the reference intensity in several analyzed regions, and that extraneous matter be judged to exist when the reflective intensity of the s-polarized light component is lower than the reference intensity in several hundred analyzed regions. In a surface inspection device as described hereinabove, an operation controlling means may nullify the detection results for an analyzed partition in which the extraneous matter judging means has determined the existence of extraneous matter. This nullification of detection results presents the unnecessary work of analyzing contamination in analyzed partitions in which extraneous matter adheres to the surface of a sample, and therefore enables an improvement in both absolute work efficiency and the accuracy of analysis of contamination.
According to another surface inspection method of the invention, a laser beam is focused and irradiated onto the surface of a sample, and the intensity is detected of at least one of the s-polarized light component and p-polarized light component of the laser beam reflected by the surface of the sample. The reflective intensity on a rough surface can be calculated by dividing this detected reflective intensity by the reflective intensity of a corresponding polarized light component on a smooth surface, and the roughness of the surface of the sample is calculated from the reflective intensity calculated by this intensity calculating means. In this surface inspection method of the invention, therefore, the roughness can be calculated from the reflective intensity of a polarized light component of the surface of the sample.
According to yet another surface inspection method of the invention, a laser beam is focused and irradiated onto the surface of a sample, and the intensities Ros and Rop of each of the s-polarized light component and p-polarized light component of the laser beam reflected by the surface of the sample are each detected. The reflective intensity at a rough surface Rou is next calculated, this being [(Rosxc3x97Rop)/(Rsxc3x97Rp)], which is the square root of the ratio of the result Rosxc3x97Rop obtained by multiplying the detected reflective intensities Ros and Rop of the s- and p-polarized light components to the result Rsxc3x97Rp obtained by multiplying the reflective intensities Rs and Rp of the s- and p-polarized light components on a smooth surface. The roughness "sgr" of the surface of the sample is then calculated from this calculated reflective intensity Rou and the wavelength xcex of the laser beam as Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex)2]. In this surface inspection method of the invention, therefore, the roughness can be calculated from the reflective intensities of polarized light components of the sample surface. In particular, surface roughness "sgr" of a sample can be calculated with good accuracy because the reflective intensity of the rough surface Rou is calculated based on both s- and p-polarized light.
The basic principles of the above-described invention are next explained. First, although self-evident from the above-described equations (1a) and (1b), reflective intensity Rou of a rough surface can be calculated even if only one of s- and p-polarized light is measured.
However, greater accuracy is achieved if reflective intensity Rou of a rough surface is calculated based on both s- and p-polarized light as in the following equation (3):
Rou={square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)]xe2x80x83xe2x80x83(3) 
Moreover, the surface of a sample, which is a microscopically rough surface, reflects a laser beam as a generally diffuse beam, as described in the foregoing explanation. The actually measured values of reflective intensities Ros and Rop of s- and p-polarized light are therefore extremely small numerical values. The actually measured values of reflective intensities Ros and Rop of s- and p-polarized light are therefore as in the following equations (4a and 4b):
Ros=Ps/Cxe2x80x83xe2x80x83(4a) 
Rop=Pp/Cxe2x80x83xe2x80x83(4b) 
Ps and Pp are the actual light quantities of incident s- and p-polarized light and C is a device constant, these values being determined based on measurements of a reference sample having a known surface roughness.
Using the above-described equations (4a) and (4b), the previously described equation (3) for reflective intensity Rou of a rough surface becomes:
Rou={{square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)]}/Cxe2x80x83xe2x80x83(5) 
The parameters of the right side of this equation (5) are all measured values or theoretical values, and reflective intensity Rou of a rough surface is thus calculated. Using statistical theory of surface roughness with this reflective intensity Rou of a rough surface and surface roughness "sgr" results in the following relation:
Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex1xcex)2]xe2x80x83xe2x80x83(6) 
The surface roughness "sgr" of a sample is thus calculated.
According to yet another surface inspection method of the invention, the reflective intensity at a rough surface Rou is calculated as {square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)] as in the above-described surface inspection method of the invention, but roughness "sgr" of the surface of a sample is calculated as Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex1xcex)2] based on this reflective intensity Rou, wavelength xcex of the laser beam, and corrective coefficient xcex1.
In the surface inspection method of this invention, therefore, roughness can be calculated from the reflective intensities of the polarized light components of the sample surface. In particular, surface roughness "sgr" of a sample can be calculated with good accuracy because reflective intensity Rou of a rough surface is calculated based on both s- and p-polarized light, and the calculation of surface roughness "sgr" of a sample is corrected by corrective coefficient xcex1.
According to still another surface inspection method of the invention, each of the reflective intensities Ros and Rop of the s-polarized light component and p-polarized light component are individually detected as in the above-described surface inspection method of the invention, and the reflective intensity Rou at a rough surface is calculated as {{square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)]}/C, which is the division, by a prescribed device constant C, of the square root of the ratio of the result Rosxc3x97Rop of multiplying the reflective intensities Rop and Rop to the result Rsxc3x97Rp of multiplying reflective intensities Rs and Rp of the s-polarized light component and p-polarized light components at a smooth surface. Roughness "sgr" of the surface of a sample is calculated from this reflective intensity Rou, the laser beam wavelength xcex, and corrective coefficient xcex1 as Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex1xcex)2].
In the surface inspection method of the invention, roughness of the surface of a sample can be calculated from the reflective intensities of the polarized light components. In particular, the surface roughness "sgr" of a sample can be calculated with good accuracy because reflective intensity Rou of a rough surface is calculated based on both s- and p-polarized light, the calculation of this reflective intensity Rou is corrected by device constant C, and the calculation of surface roughness "sgr" of the sample is corrected by corrective coefficient xcex1.
According to yet another surface inspection device of the invention, when a laser irradiating device focuses and irradiates a laser beam upon the surface of a sample held by a sample holding structure, a polarized light detector detects the intensity of at least one of the s-polarized light component and the p-polarized light component of the laser beam that is reflected by the surface of the sample. An intensity calculating means divides this detected reflective intensity by the reflective intensity of a corresponding polarized light component reflected by a smooth surface to calculate the reflective intensity of a rough surface, and a roughness detecting means calculates roughness of the surface of the sample based on this calculated reflective intensity.
In the surface inspection device of the invention, therefore, roughness can be calculated from the reflective intensity of a polarized light component of the surface of a sample.
According to still another surface inspection device of the invention, when a laser irradiating device focuses and irradiates a laser beam onto the surface of a sample that is held by a sample holding structure, a polarized light detector individually detects the intensities of each of Ros and Rop of the s-polarized light component and p-polarized light component of a laser beam that is reflected by the surface of the sample. An intensity calculating means calculates reflective intensity Rou of the rough surface as {square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)], which is the square root of the ratio of the result Rosxc3x97Rop of multiplying reflective intensities Ros and Rop of the detected s- and p-polarized light components to the result Rsxc3x97Rp of multiplying reflective intensities Rs and Rp of the s-polarized light component and p-polarized light component on a smooth surface. Roughness "sgr" of the surface of a sample is calculated as Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex)2] based on this calculated reflective intensity Rou and the laser beam wavelength xcex.
In this surface inspection device of the invention, therefore, roughness can be calculated from the reflective intensities of the polarized light components of the sample surface. In particular, surface roughness "sgr" of a sample can be calculated with good accuracy because reflective intensity Rou is calculated based on both s- and p-polarized light.
According to yet another surface inspection device of the invention, an intensity-calculating means calculates the reflective intensity Rou of a rough surface as {square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)] as in the above-described surface inspection device of the invention, and a roughness detecting means calculates roughness "sgr" of the surface of a sample as Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex1xcex)2] based on this calculated reflective intensity Rou, the laser beam wavelength xcex, and corrective coefficient xcex1.
In the surface inspection device of this invention, roughness can therefore be calculated from the reflective intensities of the polarized light components of the sample surface. In particular, surface roughness "sgr" of a sample can be calculated with good accuracy because reflective intensity Rou of a rough surface is calculated based on both s- and p-polarized light, and because the calculation of surface roughness "sgr" of the sample is corrected by corrective coefficient xcex1.
According to yet another surface inspection device of the invention, an intensity calculating means calculates reflective intensity Rou of a rough surface as Rou={{square root over ( )}[(Rosxc3x97Rop)/(Rsxc3x97Rp)]}/C as in the above-described surface inspection device of the invention, and a roughness detecting means then calculates roughness "sgr" of the surface of a sample as Rou=exp[xe2x88x92(4xcfx80"sgr"/xcex1xcex)2] based on this calculated reflective intensity Rou, laser beam wavelength xcex, and a corrective coefficient xcex1.
In this surface inspection device of the invention, roughness can therefore be calculated from the reflective intensities of the polarized light components of the surface of the sample. In particular, reflective intensity Rou of a rough surface is calculated based on both s- and p-polarized light, and the calculation of this reflective intensity Rou is corrected by device constant C, and the calculation of surface roughness "sgr" of the sample is corrected by corrective coefficient xcex1. Surface roughness "sgr" of a sample can therefore be calculated with good accuracy.
In the above-described surface inspection device, a value on the order of 0.2-0.5 is suitable as corrective coefficient xcex1 of the roughness detecting means. In this case, surface roughness "sgr" calculated as a theoretical approximate value can be corrected equivalent to the actual numerical value by means of a suitable corrective coefficient xcex1.
In a surface inspection device as described hereinabove, an intensity calculating means may calculate reflective intensities Rs and Rp of s- and p-polarized light components on a smooth surface as Rs=rsxc3x97rs* and Rp=rpxc3x97rp* based on Fresnel amplitude reflectances rs and rp and by means of complex conjugate quantity rs* and rp*.
In this case, reflective intensities Rs and Rp of s- and p-polarized light components on a smooth surface can be calculated as theoretical values. In addition, Fresnel amplitude reflectances rs and rp are functions that are dependent only on the complex dielectric constant of the metal or semiconductor that is the sample and the incident angle of the laser beam.
In the above-described surface inspection device, a relative scanning structure may move at least one of the laser irradiating device and the sample holding structure to cause the laser beam that irradiates the sample to scan two-dimensionally by prescribed analyzed regions, and an image displaying means may display, as an image that corresponds to the surface of a sample, the multiplicity of roughness values calculated for each of the multiplicity of analyzed regions. In this case, the state of roughness of the surface of a sample can be adequately confirmed by means of the displayed image.
Furthermore, each of the various means described in this invention may be formed so as to realize their functions, and may be formed as, for example, dedicated hardware, a computer provided with appropriate functions by a program, functions realized inside a computer by means of an appropriate program, or a combination of these forms.
The above and other objects, features, and advantages according to the present invention will become apparent from the following description with reference to the accompanying drawings which illustrate examples according to the present invention.